BUPT-GAMMA / Uncovering-the-Structural-Fairness-in-Graph-Contrastive-LearningLinks
Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"
☆29Updated 3 years ago
Alternatives and similar repositories for Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning
Users that are interested in Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning are comparing it to the libraries listed below
Sorting:
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆53Updated 2 years ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- ☆38Updated 3 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆86Updated 11 months ago
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- ☆27Updated 3 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆56Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆45Updated 3 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆143Updated 2 years ago
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆31Updated last year
- The source code of SpCo☆34Updated 2 years ago
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆34Updated 3 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- Awesome literature on imbalanced learning on graphs☆75Updated last year
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆33Updated last year
- This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Lea…☆17Updated 2 years ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆65Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆35Updated 2 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆61Updated 3 years ago
- ☆29Updated 4 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆44Updated 2 years ago
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆46Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 4 years ago
- [CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".☆49Updated 4 years ago
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆67Updated last year
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆69Updated last year
- Reimplementation of AAAI21 paper "Beyond Low-frequency Information in Graph Convolutional Networks" based on PyTorch and PyTorch Geometri…☆24Updated 3 years ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆89Updated last year